# mutate

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##### Mutate a data frame by adding new or replacing existing columns.

This function is very similar to transform but it executes the transformations iteratively so that later transformations can use the columns created by earlier transformations. Like transform, unnamed components are silently dropped.

##### Usage
mutate(.data, ...)
##### Arguments
.data
the data frame to transform
...
named parameters giving definitions of new columns.
##### Details

Mutate seems to be considerably faster than transform for large data frames.

subset, summarise, arrange. For another somewhat different approach to solving the same problem, see within.
library(plyr) # Examples from transform mutate(airquality, Ozone = -Ozone) mutate(airquality, new = -Ozone, Temp = (Temp - 32) / 1.8) # Things transform can't do mutate(airquality, Temp = (Temp - 32) / 1.8, OzT = Ozone / Temp) # mutate is rather faster than transform system.time(transform(baseball, avg_ab = ab / g)) system.time(mutate(baseball, avg_ab = ab / g))